A method to assist in the early diagnosis of pancreatic adenocarcinoma

Abstract

The present invention relates to a novel method for the early diagnosis of pancreatic adenocarcinoma, comprising the use of gold nanoparticles and a subsequent image analysis, a method of screening or monitoring pathological and non-pathological patients to identify pathological patients at risk of pancreatic adenocarcinoma, comprising the use of gold nanoparticles and a subsequent image analysis, a kit comprising reactants for the early diagnosis of pancreatic adenocarcinoma.

1 . A method to assist in the early diagnosis of pancreatic adenocarcinoma which allows the identification of subjects in an early state of disease or at risk of pancreatic adenocarcinoma for whom it is necessary or appropriate to carry out second-level examinations by classifying a plasma sample of these subjects according to two or more levels of risk in which the classification of said sample in at least one of said levels of risk indicates the need or opportunity to carry out second-level examinations, comprising the following steps:
 a) providing a plasma sample from a blood sample of a subject to be analyzed;   b) incubating said plasma sample with gold nanoparticles so as to allow the formation of a protein crown on said nanoparticles, said passage b) being optionally followed by a passage b′) in which the incubated material is subjected to centrifugation and one or more washes with phosphate buffer to eliminate weakly bound proteins;   c) separating the proteins that make up said protein crown from said nanoparticles;   d) subjecting said proteins to electrophoresis on a denaturing polyacrylamide gradient gel so as to obtain the protein profile (Pp) of the protein crown obtained in point b) or b′);   e) providing at least one discriminant function (ƒ(α 1 , α 2 , . . . α n ), g(α 1 , α 2 , as . . . α n )) and two or more bands of molecular weight (A 1 , A 2  . . . A n ), said at least one discriminant function (ƒ(α 1 , α 2 , . . . α n ), (g(α 1 , α 2 , α 3 , . . . α n )) and said bands of molecular weight (A 1 , A 2 , . . . A n ) being predetermined on the basis of a set of reference samples;   f) calculating an integral area value (VA 1 , VA 2  . . . VA n ) of said protein profile (Pp) for each of said bands of molecular weight (A 1 , A 2  . . . A n );   g) calculating at least one discriminant value (VD f , VD g ) of said at least one discriminant function ((α 1 , α 2 , . . . α n ), (g(α 1 , α 2 , α 3 , . . . α n )) for at least one pair of said integral area values (VA 1 , VA 2  . . . VA n );   h) classifying the plasma sample by comparing said at least one discriminant value (VD f , VD g ) with at least one predefined threshold value (VS).   
     
     
         2 . The method according to  claim 1 , wherein said second-level examinations comprise one or more among: abdomen CT, abdomen MRI, echoendoscopy, ERCP. 
     
     
         3 . The method according to  claim 1 , wherein said at least one discriminant function (ƒ(α 1 , α 2 , . . . α n ), (g(α 1 , α 2 , α 3 , . . . α n )) is obtained by linear discrimination analysis. 
     
     
         4 . The method according to  claim 1 , wherein said at least one discriminant function (ƒ(α 1 , α 2 , . . . α n ), (g(α 1 , α 2 , α 3 , . . . α n )) comprises a first function (ƒ(α 1 , α 2 )) represented by the equation of a straight line of the type:
   (α 1 ,α 2 )= r 1+ r 2*α 1   +r 3*α 2 =0
 
 in which r1, r2 and r3 are the coefficients of the line and α 1  and α 2  are integral area values. 
 
     
     
         5 . The method according to  claim 1 , wherein said at least one discriminant function (ƒ(α 1 , α 2 , . . . α n ), (g(α 1 , α 2 , α 3 , . . . α n )) comprises a second function (g(α 1 , as, α 4 )) represented by the equation of a plane of the type:
     g (α 1 ,α 3 ,α 4 )= p 1+ p 2*α 1   +p 3*α 3   +p 4*α 4 =0
 
 in which p1, p2, p3 and p4 are coefficients of the plane and α 1 , α 3  and α 4  are integral area values. 
 
     
     
         6 . The method according to  claim 1 , wherein said two or more bands of molecular weight (A 1 , A 2  . . . A n ) are determined so that each peak—corresponding to a respective electrophoretic band—of each protein profile of the set of reference samples belongs to one and only one of said bands. 
     
     
         7 . The method according to  claim 1 , wherein said at least one predefined threshold value (VS) is equal to zero and said plasma sample is classified as at risk if the discriminant value (VD f , VD g ) is greater than zero. 
     
     
         8 . The method according to  claim 1 , wherein said bands of molecular weight can be, for example, two or more among A 1 : 10-20 kDa; A 2 : 20-25 kDa; A 3 : 25-35 kDa; A 4 : 35-45 kDa. 
     
     
         9 . The method according to  claim 1 , said gold nanoparticles have an average diameter of 100 nm. 
     
     
         10 . The method according to  claim 1 , wherein step b) is carried out at a temperature between 35 and 40° C. for a period of time between 40 and 120 minutes. 
     
     
         11 . The method according to  claim 10 , wherein said temperature is 37° C. and/or said time is 55 to 56 minutes. 
     
     
         12 . The method according to  claim 1 , wherein said step b) is followed by a step b′) in which the incubated material is subjected to centrifugation and one or more washes with phosphate buffer to eliminate weakly bound proteins. 
     
     
         13 . The method according to  claim 1 , wherein said separation at point c) is carried out by boiling for about 10 minutes the gold particles as obtained in point b) or b′) suspended in polyacrylamide gel charge buffer comprising SOS. 
     
     
         14 . The method according to  claim 1 , wherein said polyacrylamide gradient is a 4-20% gradient. 
     
     
         15 . A computer program comprising code adapted to carry out steps e) to h)
 e) providing at least one discriminant function (ƒ(α 1 , α 2 , . . . α n ), (g(α 1 , α 2 , α 3 , . . . α n )) and two or more bands of molecular weight (A 1 , A 2  . . . A n ), said at least one discriminant function (ƒ(α 1 , α 2 , . . . α n ), (g(α 1 , α 2 , α 3 , . . . α n )) and said bands of molecular weight (A 1 , A 2 , . . . A n ) being predetermined on the basis of a set of reference samples;   f) calculating an integral area value (VA 1 , VA 2  . . . VA n ) of said protein profile (Pp) for each of said bands of molecular weight (A 1 , A 2  . . . A n );   g) calculating at least one discriminant value (VD f , VD g ) of said at least one discriminant function ((α 1 , α 2 , . . . α n ), (g(α 1 , α 2 , α 3 , . . . α n )) for at least one pair of said integral area values (VA 1 , VA 2  . . . VA n );   h) classifying a plasma sample by comparing said at least one discriminant value (VD f , VD g ) with at least one predefined threshold value (VS)   
       when executed on a computer. 
     
     
         16 . A storage medium comprising the program according to  claim 15 . 
     
     
         17 . A kit comprising one or more aliquots of one or more reactants adapted to carry out steps a) to d) and optionally b′) and a storage medium according to  claim 16  to assist in the early diagnosis of pancreatic adenocarcinoma that allows the identification of subjects in an early state of disease or at risk of pancreatic adenocarcinoma for whom it is necessary or appropriate to carry out second-level examinations.